To meet climate targets, power generation capacity from photovoltaics (PV) in 2030 will have to be much greater than is predicted from either steady state growth using today's manufacturing capacity or industry roadmaps. Analysis of whether current technology can scale, in an economically sustainable way, to sufficient levels to meet these targets has not yet been undertaken, nor have tools to perform this analysis been presented. Here, we use bottom-up cost modeling to predict cumulative capacity as a function of technological and economic variables. We find that today's technology falls short in two ways: profits are too small relative to upfront factory costs to grow manufacturing capacity rapidly enough to meet climate targets, and costs are too high to generate enough demand to meet climate targets. We show that decreasing the capital intensity (capex) of PV manufacturing to increase manufacturing capacity and effectively reducing cost (e.g., through higher efficiency) to increase demand are the most effective and least risky ways to address these barriers to scale. We also assess the effects of variations in demand due to hard-to-predict factors, like public policy, on the necessary reductions in cost. Finally, we review examples of redundant technology pathways for crystalline silicon PV to achieve the necessary innovations in capex, performance, and price. Broader context To reduce CO 2 emissions enough over the next fifteen years and avoid the worst effects of climate change will require dramatic increases in the deployment of renewable energy, photovoltaics (PV) in particular. Climate action plans call for 2-10 terawatts (TW) of PV by 2030. Current manufacturing capacity could supply enough for 1 TW of cumulative installations at the end of this period, implying that growth in manufacturing capacity is necessary. Industry roadmaps project up to 2.6 TW but largely fail to assess whether these targets are economically feasible with today's PV module technology. Addressing the question of what technological innovations, if any, would enable rapid manufacturing scale-up requires a conceptual advance in modeling methodology. We address this challenge by coupling three industry-validated models: a bottom-up cost model, an economically sustainable growth-rate calculator, and a constraining demand curve. This approach enables us to determine the sensitivity of PV industry growth to specific technological and economic variables, considering both their effect on the ratio of up-front factory costs to revenue and demand as a function of PV module price. Shifting the demand curve enables us to consider the effects of different policy decisions, like a carbon tax or deployment subsidies.